Abstract

The Microsoft HoloLens is one of the latest headsets that facilitates mixed and augmented reality (AR) applications. It has a high potential to leverage AR applications in many domains. However, the first version also comes with several limitations such as the limited battery lifetime and the small field of view. An important one is the lack of high-fidelity depth data which would facilitate object detection and tracking research; a capability imperative for many applications. To mitigate this limitation, we integrated the HoloLens into a point cloud-based tracking system. Our system uses several Kinect range cameras to obtain a point cloud and to detect and track real assets of interest in this point cloud. The pose data for all objects are forwarded to the HoloLens, which can then render 3D models from the right perspective. However, this system is not free of tolerances and tracking errors, which mandates calibrations. This poster explains how the system was set-up and verifies the feasibility of a system such as this for 3D model registration using the HoloLens as a display device.